A new multi-position calibration method for MEMS inertial navigation systems
TL;DR: A new multi-position calibration method was designed for MEMS of high to medium quality that has been adapted to compensate for the primary sensor errors, including the important scale factor and non-orthogonality errors of the gyroscopes.
Abstract: The Global Positioning System (GPS) is a worldwide navigation system that requires a clear line of sight to the orbiting satellites For land vehicle navigation, a clear line of sight cannot be maintained all the time as the vehicle can travel through tunnels, under bridges, forest canopies or within urban canyons In such situations, the augmentation of GPS with other systems is necessary for continuous navigation Inertial sensors can determine the motion of a body with respect to an inertial frame of reference Traditionally, inertial systems are bulky, expensive and controlled by government regulations Micro-electro mechanical systems (MEMS) inertial sensors are compact, small, inexpensive and most importantly, not controlled by governmental agencies due to their large error characteristics Consequently, these sensors are the perfect candidate for integrated civilian navigation applications with GPS However, these sensors need to be calibrated to remove the major part of the deterministic sensor errors before they can be used to accurately and reliably bridge GPS signal gaps A new multi-position calibration method was designed for MEMS of high to medium quality The method does not require special aligned mounting and has been adapted to compensate for the primary sensor errors, including the important scale factor and non-orthogonality errors of the gyroscopes A turntable was used to provide a strong rotation rate signal as reference for the estimation of these errors Two different quality MEMS IMUs were tested in the study The calibration results were first compared directly to those from traditional calibration methods, eg six-position and rate test Then the calibrated parameters were applied in three datasets of GPS/INS field tests to evaluate their accuracy indirectly by comparing the position drifts during short-term GPS signal outages
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TL;DR: A survey of the information sources and information fusion technologies used in current in-car navigation systems is presented and the pros and cons of the four commonly used information sources are described.
Abstract: In-car positioning and navigation has been a killer application for Global Positioning System (GPS) receivers, and a variety of electronics for consumers and professionals have been launched on a large scale. Positioning technologies based on stand-alone GPS receivers are vulnerable and, thus, have to be supported by additional information sources to obtain the desired accuracy, integrity, availability, and continuity of service. A survey of the information sources and information fusion technologies used in current in-car navigation systems is presented. The pros and cons of the four commonly used information sources, namely, 1) receivers for radio-based positioning using satellites, 2) vehicle motion sensors, 3) vehicle models, and 4) digital map information, are described. Common filters to combine the information from the various sources are discussed. The expansion of the number of satellites and the number of satellite systems, with their usage of available radio spectrum, is an enabler for further development, in combination with the rapid development of microelectromechanical inertial sensors and refined digital maps.
524 citations
Cites background from "A new multi-position calibration me..."
...The fixed terms, and, to a large extent, the temperature varying terms, can be estimated and compensated by calibration of the sensors (see [65]–[70] for several calibration approaches)....
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TL;DR: A systematic review of studies using accelerometers, gyroscopes and/or magnetometers to analyse sport motor-tasks performed by athletes and indications on the reliability of sensor-based performance indicators are provided.
Abstract: Recent technological developments have led to the production of inexpensive, non-invasive, miniature magneto-inertial sensors, ideal for obtaining sport performance measures during training or competition. This systematic review evaluates current evidence and the future potential of their use in sport performance evaluation. Articles published in English (April 2017) were searched in Web-of-Science, Scopus, Pubmed, and Sport-Discus databases. A keyword search of titles, abstracts and keywords which included studies using accelerometers, gyroscopes and/or magnetometers to analyse sport motor-tasks performed by athletes (excluding risk of injury, physical activity, and energy expenditure) resulted in 2040 papers. Papers and reference list screening led to the selection of 286 studies and 23 reviews. Information on sport, motor-tasks, participants, device characteristics, sensor position and fixing, experimental setting and performance indicators was extracted. The selected papers dealt with motor capacity assessment (51 papers), technique analysis (163), activity classification (19), and physical demands assessment (61). Focus was placed mainly on elite and sub-elite athletes (59%) performing their sport in-field during training (62%) and competition (7%). Measuring movement outdoors created opportunities in winter sports (8%), water sports (16%), team sports (25%), and other outdoor activities (27%). Indications on the reliability of sensor-based performance indicators are provided, together with critical considerations and future trends.
314 citations
TL;DR: In this article, the authors present methods to calibrate and compensate for non-zero biases, non-unit scale factors, axis misalignments and cross-axis sensitivities of both the tri-axial accelerometer and gyroscopic setups in a microelectro-mechanical systems (MEMS) based inertial measurement unit (IMU).
Abstract: This paper presents methods to calibrate and compensate for non-zero biases, non-unit scale factors, axis misalignments and cross-axis sensitivities of both the tri-axial accelerometer and gyroscopic setups in a micro-electro-mechanical systems (MEMS) based inertial measurement unit (IMU). These methods depend on the Earth's gravity as a stable physical calibration standard. Specifically, the calibration of gyroscopes is significantly improved by comparing the outputs of the accelerometer and the IMU orientation integration algorithm, after arbitrary motions. The derived property and proposed cost function allow the gyroscopes to be calibrated without external equipment, such as a turntable, or requiring precise maneuvers. Both factors allow the IMU to be easily calibrated by the user in the field so that it can function as an accurate orientation sensor. A custom-made prototype IMU is used to demonstrate the effectiveness of the proposed methods, with data that are carefully obtained using prescribed motions, as well as those less rigorously collected from the IMU when it is mounted on the head of a user or held in hands with brief random movements. With calibration, the observed average static angular error is less than a quarter of a degree and the dynamic angular error is reduced by a factor of 2 to 5.
226 citations
01 May 2014
TL;DR: A robust and quick calibration protocol that exploits an effective parameterless static filter to reliably detect the static intervals in the sensor measurements, where it is assumed local stability of the gravity's magnitude and stable temperature.
Abstract: Motion sensors as inertial measurement units (IMU) are widely used in robotics, for instance in the navigation and mapping tasks. Nowadays, many low cost micro electro mechanical systems (MEMS) based IMU are available off the shelf, while smartphones and similar devices are almost always equipped with low-cost embedded IMU sensors. Nevertheless, low cost IMUs are affected by systematic error given by imprecise scaling factors and axes misalignments that decrease accuracy in the position and attitudes estimation. In this paper, we propose a robust and easy to implement method to calibrate an IMU without any external equipment. The procedure is based on a multi-position scheme, providing scale and misalignments factors for both the accelerometers and gyroscopes triads, while estimating the sensor biases. Our method only requires the sensor to be moved by hand and placed in a set of different, static positions (attitudes). We describe a robust and quick calibration protocol that exploits an effective parameterless static filter to reliably detect the static intervals in the sensor measurements, where we assume local stability of the gravity's magnitude and stable temperature. We first calibrate the accelerometers triad taking measurement samples in the static intervals. We then exploit these results to calibrate the gyroscopes, employing a robust numerical integration technique. The performances of the proposed calibration technique has been successfully evaluated via extensive simulations and real experiments with a commercial IMU provided with a calibration certificate as reference data.
186 citations
Cites methods from "A new multi-position calibration me..."
...Finally, we define a body frame (BF), which is an orthogonal frame that represents, for example, the coordinate frame of the IMU’s chassis....
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TL;DR: This paper presents an efficient method for calibrating the magnetic compass without the aforementioned traditional requirements, based on the fact that the error model of magnetic compass is an ellipsoid, and a constraint least-square method is adopted to estimate the parameters of an ellIPsoid by rotating the compass in various (random) orientations.
Abstract: Magnetic compass is widely used to indicate the heading of vehicle by measuring the Earth's magnetic field. However, it suffers from local magnetic interferences; thus, the calibration of the magnetic compass is very essential before it is used. The traditional calibration methods require reference information and special requirements such as keeping the magnetic compass level during calibration, which is very difficult to manage outdoor. This paper presents an efficient method for calibrating the magnetic compass without the aforementioned traditional requirements. This method is based on the fact that the error model of magnetic compass is an ellipsoid, and a constraint least-square method is adopted to estimate the parameters of an ellipsoid by rotating the magnetic compass in various (random) orientations. This method can estimate all the parameters of the error model and compensate errors caused by sensor defects, hard-iron interferences, and soft-iron interferences. Although the calibration parameters are relative values, it does not have any influence on the heading calculated. The experimental results show that this method is effective in calibrating the magnetic compass, and the heading precision of the magnetic compass acquired after calibration is better than 0.4°.
169 citations
Cites methods from "A new multi-position calibration me..."
...These methods are similar to each other [19], [20]....
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References
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Book•
01 Jan 1997
TL;DR: In this paper, the physical principles of inertial navigation, the associated growth of errors and their compensation, and their application in a broad range of applications are discussed, drawing current technological developments and providing an indication of potential future trends.
Abstract: Inertial navigation is widely used for the guidance of aircraft, missiles ships and land vehicles, as well as in a number of novel applications such as surveying underground pipelines in drilling operations. This book discusses the physical principles of inertial navigation, the associated growth of errors and their compensation. It draws current technological developments, provides an indication of potential future trends and covers a broad range of applications. New chapters on MEMS (microelectromechanical systems) technology and inertial system applications are included.
2,536 citations
"A new multi-position calibration me..." refers background or methods in this paper
...The six-position static and rate tests are among the most commonly used (Titterton and Weston 1997) calibration methods....
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...Navigation, by definition, provides the best possible estimate of a moving object in terms of its position, velocity and attitude (Titterton and Weston 1997)....
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Book•
29 Dec 2000
TL;DR: The authors explore the various subtleties, common failures, and inherent limitations of the theory as it applies to real-world situations, and provide numerous detailed application examples and practice problems, including GNSS-aided INS, modeling of gyros and accelerometers, and SBAS and GBAS.
Abstract: An updated guide to GNSS and INS, and solutions to real-world GPS/INS problems with Kalman filtering Written by recognized authorities in the field, this second edition of a landmark work provides engineers, computer scientists, and others with a working familiarity with the theory and contemporary applications of Global Navigation Satellite Systems (GNSS), Inertial Navigational Systems (INS), and Kalman filters. Throughout, the focus is on solving real-world problems, with an emphasis on the effective use of state-of-the-art integration techniques for those systems, especially the application of Kalman filtering. To that end, the authors explore the various subtleties, common failures, and inherent limitations of the theory as it applies to real-world situations, and provide numerous detailed application examples and practice problems, including GNSS-aided INS, modeling of gyros and accelerometers, and SBAS and GBAS. Drawing upon their many years of experience with GNSS, INS, and the Kalman filter, the authors present numerous design and implementation techniques not found in other professional references. This Second Edition has been updated to include: GNSS signal integrity with SBAS Mitigation of multipath, including results Ionospheric delay estimation with Kalman filters New MATLAB programs for satellite position determination using almanac and ephemeris data and ionospheric delay calculations from single and dual frequency data New algorithms for GEO with L1 /L5 frequencies and clock steering Implementation of mechanization equations in numerically stable algorithms To enhance comprehension of the subjects covered, the authors have included software in MATLAB, demonstrating the working of the GNSS, INS, and filter algorithms. In addition to showing the Kalman filter in action, the software also demonstrates various practical aspects of finite word length arithmetic and the need for alternative algorithms to preserve result accuracy.
1,650 citations
Book•
01 Jan 1997
TL;DR: In this article, a central force gravity field model is used for inertial navigation with assistance from external measurements. But this model is not suitable for the Kalman Filter State Variable Error Models.
Abstract: Part 1 Inertial Navigation: Notation, Coordinate Systems and Units Equations of Motion in a Central Force Gravity Field Inertial Instrumentation Calibration Initial Alignment and Attitude Computation Geodetic Variables and Constants Equations of Motion with General Gravity Model. Part 2 Inertial Navigation with Aids: Inertial Navigation with External Measurements Error Equations for the Kalman Filter State Variable Error Models. Part 3 Accuracy Analysis: Accuracy Criteria and Analysis Techniques Error Equations for Calibration, Alignment and Initialization Evaluation of Gravity Model Error Effects. Appendices: Matrix Inverse Formulas LaPlace Transforms Quaternions Associated Legendre Functions Associated Legendre Function Derivatives Procedure for Generating Gravity Disturbance Realizations Procedure for Generating Specific Force Profile.
470 citations
"A new multi-position calibration me..." refers background or methods in this paper
...In Shin and El-Sheimy (2002) this problem was not addressed, but it will be shown in the following sections that for MEMS sensors these errors can contribute largely to the overall position error during prediction periods....
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...(a) Misaligned orthogonal sensor triad with respect to the local level frame (after Shin and El-Sheimy (2002))....
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...Another issue with the multi-position calibration method for MEMS IMUs is that it is difficult to converge to reasonable bias and scale factor values for MEMS sensors without an initial rough estimate of these error values. This is due to the large parameter variation of these sensors. To provide approximate starting values for the biases and scale factors of the accelerometers, the positions closest to face up and face down configurations were used in the modified multi-position method. The reason these are only approximate values is due to the rough installation of these positions with respect to the vertical gravity vector; a perfect cube was not used as in the six-position static calibration. For the starting value of the gyroscopes, any static output can be regarded as the gyro bias since the earth rotation is negligible compared to the original gyro biases. In summary, the modified multi-position method has the following two differences than the previously published paper by Shin and El-Sheimy (2002) for use with low cost MEMS inertial sensors:...
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...Angular rate tests are used for calibrating the biases, scale factors and non-orthogonalities of the gyroscopes for lower grade navigation systems. If the rate tests and the improved six-position static method are used together, one can determine all the error components even for low cost sensors. Rate tests are typically done using a precise rate turntable. By rotating the unit through given turning rates and comparing the outputs of the IMU to these references, the biases, scale factors and non-orthogonalities can be estimated. This is typically accomplished by rotating the table through a defined angular rate in both the clockwise and counter clockwise directions. A third method of calibration uses precise alignment of a multi-axis turntable to the local level frame (LLF). The IMU is mounted on the aligned turntable and then the unit is rotated through a series of accurately known angles and positioned in different orientations with respect to the LLF. This technique makes use of the gravity and earth rotation rates as references (El-Sheimy 2006). Again similar to the sixposition method, precise alignment with the local level frame is the main requirement and therefore even small orientation errors will contaminate the error estimates. Also, similar to the six-position method, LLF calibration for MEMS suffers from the fact that the earth rotation is a very weak signal and is typically buried within the sensor noise for low grade inertial sensors. This paper will explore a recent calibration method for strapdown IMU systems. This method, first described in Shin and El-Sheimy (2002), does not require precise alignment of the IMU axes and can be applied in the field for correcting changing sensor errors such as biases....
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30 Jan 2002
TL;DR: Some of the techniques that overcome the limitations of lowcost IMUs are introduced, i.e. the in-filed calibration, the velocity matching alignment, and the use of non-holonomic constraints.
Abstract: High performance Inertial Navigation Systems (INSs) provide continuously very accurate attitude, velocity and position information.
However, it is usually very expensive and because the navigation solutions are obtained by integration, they drift at low frequencies. To obtain very accurate outputs at all frequencies, the INS should be updated periodically using external measurements. On the other hand, the GPS measurements, under ideal conditions, are consistent in accuracy throughout a survey mission. However, such conditions do not often exist.
Independent GPS navigation requires at least four satellites with good geometry. The major drawback of GPS is, therefore, the accuracy degradation due to poor satellite geometry, cycle slips, satellite outages, and dynamic lag during maneuvers. This is especially prevalent in urban centres and when encountering highway overpasses/tunnels. Because of their complementary characteristics, INS is often integrated
with GPS. The integration of GPS and INS provides a system that has superior performance in comparison with either a GPS or an INS stand-alone system. For instance, GPS derived positions have approximately white noise characteristics over the whole frequency range. The GPS-derived positions and velocities are therefore excellent external measurements for updating the INS, thus improving its long-term accuracy.
Similarly, the INS can provide precise position and velocity data for GPS signal acquisition and reacquisition after outages. Recently, focus has been made on developing integrated GPS and low-cost inertial measuring units (IMUs) for commercial applications, for example car navigation. However, due to the low quality of the IMU, huge amount of navigation errors can be generated in very short time intervals. Therefore, low-cost IMUs have shown to be usable only for few seconds
without additional aiding. Furthermore due to the large drift rate of the gyros used in low-cost IMUs, self-alignment cannot be applied for some systems. This paper introduces some of the techniques that overcome the limitations of lowcost IMUs, i.e. the in-filed calibration, the velocity matching alignment, and the use of non-holonomic constraints.
Tests were conducted using the NovAtel Black Diamond System (BDSTM). A new field calibration method was developed and tested successfully. The new calibration method does not require the IMU to be aligned to the local level frame. Furthermore, the bias estimation of the calibration
method is not affected by the reference gravity error. Almost half of the positioning error could be removed with the accelerometer calibration information. The mechanization and navigation Kalman filter were implemented based on the navigation frame to test the velocity matching alignment and non-holonomic constraints. The velocity matching
alignment technique was tested for the IMUs to which stationary alignment technique cannot be applied. All attitude components converged within three minutes with RMS 0.03. Non-holonomic constraints dramatically reduced the horizontal positioning error, within 40 m for 20 minutes operation. Therefore, low cost INSs can be used as a stand-alone positioning system during the GPS outages of over 10 minutes.
332 citations
01 Jan 2004
133 citations
"A new multi-position calibration me..." refers background in this paper
...Similarly, the bias and scale factor of a superior quality gyroscope can be estimated when the average of the static value is used in equation (8) for at least 10–15 min (Hou 2004)....
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...(9) Similarly, the bias and scale factor of a superior quality gyroscope can be estimated when the average of the static value is used in equation (8) for at least 10–15 min (Hou 2004)....
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